Implementing a cache with distributed serialization using Jackson and HashMap in Java

23 Oct 2023

caching

Caching is an effective technique to improve the performance of an application by storing frequently accessed or computed data in memory, which can be retrieved quickly. In this article, we will explore how to implement a cache using the Jackson library for distributed serialization and a HashMap in Java.

Introduction
Setting Up Dependencies
Implementing the Cache
Serializing and Deserializing Objects
Conclusion
References

Introduction

Serialization is the process of converting an object into a byte stream, which can be stored or transmitted over a network. Jackson is a popular Java library for JSON serialization and deserialization. By combining Jackson with a HashMap, we can implement a cache that can store objects and retrieve them efficiently.

Setting Up Dependencies

To start, we need to include the Jackson library in our project. We can add the following dependency to our pom.xml file for Maven:

<dependency>
    <groupId>com.fasterxml.jackson.core</groupId>
    <artifactId>jackson-databind</artifactId>
    <version>2.12.5</version>
</dependency>

If you are using a build tool other than Maven, you can check the official Jackson website for installation instructions.

Implementing the Cache

We can create a cache using a HashMap in Java. The cache will have a set capacity to limit the number of objects stored. When the cache reaches its capacity, it will evict the least recently used object to make room for a new object.

import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.ObjectMapper;

import java.util.HashMap;
import java.util.Map;

public class Cache {
    private final int capacity;
    private final Map<String, Object> cache;
    private final ObjectMapper objectMapper;

    public Cache(int capacity) {
        this.capacity = capacity;
        this.cache = new HashMap<>();
        this.objectMapper = new ObjectMapper();
    }

    public void put(String key, Object value) throws JsonProcessingException {
        if (cache.size() == capacity) {
            String leastRecentlyUsed = cache.keySet().iterator().next();
            cache.remove(leastRecentlyUsed);
        }
        String serializedValue = objectMapper.writeValueAsString(value);
        cache.put(key, serializedValue);
    }

    public Object get(String key) throws JsonProcessingException {
        if (cache.containsKey(key)) {
            String serializedValue = cache.get(key);
            return objectMapper.readValue(serializedValue, Object.class);
        }
        return null;
    }
}

In the above code, we create a Cache class that takes a capacity parameter in its constructor. The cache is implemented using a HashMap, with the key representing the object’s identifier, and the value representing the serialized object. We use the ObjectMapper class from Jackson to handle the serialization and deserialization.

The put method adds objects to the cache. If the cache is already at its capacity, it removes the least recently used object before adding the new object. The get method retrieves the object from the cache if it exists.

Serializing and Deserializing Objects

The ObjectMapper class from Jackson handles the serialization and deserialization of objects. To use it, we need to ensure that the objects we want to cache are serializable.

public class Person {
    private String name;
    private int age;

    // getters and setters
}

In the above code, let’s assume we have a Person class that we want to cache. To make the Person class serializable with Jackson, we need to add the necessary annotations:

import com.fasterxml.jackson.annotation.JsonProperty;

public class Person {
    @JsonProperty("name")
    private String name;

    @JsonProperty("age")
    private int age;

    // getters and setters
}

By adding the @JsonProperty annotation to the fields of the Person class, we tell Jackson to serialize and deserialize them using the specified property names.

Conclusion

By implementing a cache with distributed serialization using Jackson and a HashMap in Java, we can improve the performance of our application by storing frequently accessed or computed data in memory. Jackson’s serialization and deserialization capabilities make it easy to handle object caching effectively.

In this article, we explored the concepts of caching, serialization, and deserialization, and provided an example implementation using Jackson. You can further enhance the cache by adding features such as expiration time, TTL (Time to Live) support, or using a different data structure for more efficient caching.

References

Jackson Documentation #java #caching

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